Novel imputation methods under stratified simple random sampling

Anoop Kumar; Shashi Bhushan; Manahil Sid Ahmed Mustafa; Ramy Aldallal; Hassan M. Aljohani; Fatimah A. Almulhim

doi:10.1016/j.aej.2024.03.088

Novel imputation methods under stratified simple random sampling

Anoop Kumar, Shashi Bhushan, Manahil Sid Ahmed Mustafa, Ramy Aldallal, Hassan M. Aljohani, Fatimah A. Almulhim

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5 Scopus citations

Abstract

This paper addresses some classes of combined and separate imputation methods (CSIMs) of the population mean under stratified simple random sampling (SSRS) along with their characteristics. To the best of our knowledge, these imputation methods (IMs) have yet not been studied by any author under SSRS, hence these IMs are called ‘novel’. In addition, the existing CSIMs are distinguished as the members of the suggested CSIMs, respectively. The theoretical conditions under which the proposed IMs perform better are obtained by comparing the proposed IMs with the existing IMs. To validate the theoretical findings, the numerical and simulation studies are conducted on real and artificial populations, respectively.

Original language	English
Pages (from-to)	236-246
Number of pages	11
Journal	Alexandria Engineering Journal
Volume	95
DOIs	https://doi.org/10.1016/j.aej.2024.03.088
State	Published - May 2024

Keywords

Imputation
Missing values
Stratified simple random sampling

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10.1016/j.aej.2024.03.088

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title = "Novel imputation methods under stratified simple random sampling",

abstract = "This paper addresses some classes of combined and separate imputation methods (CSIMs) of the population mean under stratified simple random sampling (SSRS) along with their characteristics. To the best of our knowledge, these imputation methods (IMs) have yet not been studied by any author under SSRS, hence these IMs are called {\textquoteleft}novel{\textquoteright}. In addition, the existing CSIMs are distinguished as the members of the suggested CSIMs, respectively. The theoretical conditions under which the proposed IMs perform better are obtained by comparing the proposed IMs with the existing IMs. To validate the theoretical findings, the numerical and simulation studies are conducted on real and artificial populations, respectively.",

keywords = "Imputation, Missing values, Stratified simple random sampling",

author = "Anoop Kumar and Shashi Bhushan and Mustafa, \{Manahil Sid Ahmed\} and Ramy Aldallal and Aljohani, \{Hassan M.\} and Almulhim, \{Fatimah A.\}",

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year = "2024",

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doi = "10.1016/j.aej.2024.03.088",

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volume = "95",

pages = "236--246",

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T1 - Novel imputation methods under stratified simple random sampling

AU - Kumar, Anoop

AU - Bhushan, Shashi

AU - Mustafa, Manahil Sid Ahmed

AU - Aldallal, Ramy

AU - Aljohani, Hassan M.

AU - Almulhim, Fatimah A.

PY - 2024/5

Y1 - 2024/5

N2 - This paper addresses some classes of combined and separate imputation methods (CSIMs) of the population mean under stratified simple random sampling (SSRS) along with their characteristics. To the best of our knowledge, these imputation methods (IMs) have yet not been studied by any author under SSRS, hence these IMs are called ‘novel’. In addition, the existing CSIMs are distinguished as the members of the suggested CSIMs, respectively. The theoretical conditions under which the proposed IMs perform better are obtained by comparing the proposed IMs with the existing IMs. To validate the theoretical findings, the numerical and simulation studies are conducted on real and artificial populations, respectively.

AB - This paper addresses some classes of combined and separate imputation methods (CSIMs) of the population mean under stratified simple random sampling (SSRS) along with their characteristics. To the best of our knowledge, these imputation methods (IMs) have yet not been studied by any author under SSRS, hence these IMs are called ‘novel’. In addition, the existing CSIMs are distinguished as the members of the suggested CSIMs, respectively. The theoretical conditions under which the proposed IMs perform better are obtained by comparing the proposed IMs with the existing IMs. To validate the theoretical findings, the numerical and simulation studies are conducted on real and artificial populations, respectively.

KW - Imputation

KW - Missing values

KW - Stratified simple random sampling

UR - http://www.scopus.com/inward/record.url?scp=85189553649&partnerID=8YFLogxK

U2 - 10.1016/j.aej.2024.03.088

DO - 10.1016/j.aej.2024.03.088

M3 - Article

AN - SCOPUS:85189553649

SN - 1110-0168

VL - 95

SP - 236

EP - 246

JO - Alexandria Engineering Journal

JF - Alexandria Engineering Journal

ER -

Novel imputation methods under stratified simple random sampling

Abstract

Keywords

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